Note: The job is a remote job and is open to candidates in USA. Webstaurant Store is the world’s largest online restaurant supply company. The company is seeking a Data Scientist to provide statistical rigor for analytics projects, uncover actionable insights, and identify opportunities for growth and optimization. The role focuses on marketing measurement, experimentation, attribution modeling, and translating complex data science findings into business decisions.
Responsibilities
- Advising on analysis and modeling techniques, selecting the best fit for structured & unstructured, complex data, and developing custom analytics models to generate insights that drive value for our customers and unlock competitive advantage for our organization
- Collaborating with our analytics engineers to gather the right information from various sources so that you can implement advanced statistical methodologies and design interventions to optimize our business performance
- Conducting exploratory analysis including hypothesis testing, statistical inference, and statistical analysis (predictive and/or prescriptive)
- Maintaining and updating our in-house Media Mix Models (MMM) and Multi-Touch Attribution (MTA) models to ensure they reflect the current state of marketing spend and value
- Designing, implementing, and analyzing lift / blackout / other experiments to continually improve our attribution models
- Partnering with business and technical stakeholders, including our Google account team, to translate complex retail challenges into data science solutions
- Developing processes and tools that monitor, analyze and continuously improve model performance and data accuracy
- Work with other data scientists to design and implement experiments and glean actionable insights from experimental analyses
- Defend and explain the validity of predictive/ML models to those without a background in data science or statistics
- Actively research new tools and technologies, staying on top of analytics news and best practices
Skills
- Access to a reliable and secure high-speed internet connection. Cable or fiber internet connections (at least 75mbps download/10mbps upload) are preferred, as satellite connections often cannot support the technologies used to perform day-to-day tasks
- Access to a home router and modem
- A dedicated home office space that is noise- and distraction-free. The space should have strong wireless connection or a wired Ethernet connection (wired connection is preferred, if possible)
- A valid, physical address (apartment, suite, etc.). PO Boxes are not supported, as a physical address is required for you to receive your computer equipment
- The desire and ability to work and communicate with other team members via chat, webcam, etc
- Legal residents of one of the following states: (AK, AL, AR, AZ, CT, DE, FL, GA, IA, ID, IN, KS, KY, LA, MD, ME, MI, MN, MO, MS, MT, NC, ND, NE, NH, NM, NV, OH, OK, PA, SC, SD, TN, TX, UT, VA, VT, WI, WV, and WY)
- We only accept W-2 candidates, H-1B sponsorship is not available
- Minimum 2 years of professional experience in Data Science, or a PhD in mathematics, statistics, economics, or a related quantitative field
- Advanced proficiency in Python and SQL, with strong foundation in statistical methods and advanced modeling techniques applied to marketing and growth problems
- Hands-on experience with experimentation and causal inference frameworks, including incrementality testing, geo experiments, holdout designs, or quasi-experimental methods
- Proven ability to partner with paid marketing teams to design, execute, and analyze experiments that inform budget allocation and channel strategy
- Experience building, evaluating, or refining Media Mix Models (MMM) and/or Multi-Touch Attribution (MTA) models to quantify marketing impact and reduce uncertainty
- Ability to translate complex model outputs into clear, credible insights that drive stakeholder buy-in and influence marketing decision-making, even without direct ownership of spend
- Comfortable navigating trade-offs between model rigor, business timelines, and practical adoption by paid media stakeholders
- This role does not require a degree. We value relevant skills and experience and alignment with our core values above all else
- Ability to explain ideas simply and confidently to team members both written and verbally
- Familiarity with a variety of supervised/unsupervised/reinforcement learning methods
- Demonstrable portfolio (git repos, kaggle competitions, etc) of machine learning projects
- You have proven ability as a full stack data scientist who develops, experiments, optimizes, and scales models for the production environment
- You connect the how and why, using your knowledge of data science theories and methodologies to derive the best approach that is fit-for-purpose
Benefits
- Remote work available in eligible U.S. states
- Computer equipment provided for remote employees
Company Overview